Awesome-Multimodal-Large-Language-Models and Awesome-Multimodal-LLM
These are ecosystem siblings, as both projects curate lists of resources related to multimodal large language models, with BradyFU's being a broader collection of latest advances and HenryHZY's focusing more specifically on LLM-guided multimodal learning trends.
About Awesome-Multimodal-Large-Language-Models
BradyFU/Awesome-Multimodal-Large-Language-Models
:sparkles::sparkles:Latest Advances on Multimodal Large Language Models
Comprehensive curated repository of research papers, datasets, and benchmarks covering multimodal LLM advances across instruction tuning, hallucination mitigation, and reasoning tasks. Features proprietary evaluation frameworks (MME, Video-MME, MME-RealWorld) and the VITA series of omni-modal models supporting real-time vision-speech interaction and embodied reasoning. Targets the broader MLLM research ecosystem with extensive documentation of 750+ references and curated resources for model development and evaluation.
About Awesome-Multimodal-LLM
HenryHZY/Awesome-Multimodal-LLM
Research Trends in LLM-guided Multimodal Learning.
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work